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Record W4402541332 · doi:10.1093/jas/skae234.203

320 Ninety-nine years of accomplishment by Canadian Animal Scientists

2024· article· en· W4402541332 on OpenAlexaffabout
Tim A. McAllister, G.B. Penner

Bibliographic record

VenueJournal of Animal Science · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of SaskatchewanAgriculture and Agri-Food Canada
Fundersnot available
KeywordsBiology

Abstract

fetched live from OpenAlex

Abstract The earliest ancestor of the Canadian Journal of Animal Science traces back to the Western Canada Society of Agronomy which was established in 1918. The Western Canada Society of Animal Production was formed in 1925 and the Eastern Society was established in 1926. These were the first vestiges of the Canadian Society of Animal Production which arose as result of the amalgamation of the chapters in 1951. The Agricultural Institute of Canada established the journal “Scientific Agriculture” in 1921, which was renamed the Canadian Journal of Agricultural Science in 1953. In 1957, the journal was split into plant, soil and animal sections and the Canadian Journal of Animal Science (CJAS) became the official publication of the Canadian Society of Animal Science (CSAS). Selecting the top Canadian animal scientists over the last 99 yr is no easy task and is marked with biases and subjectivity. Time is a major consideration, as in general contributions become less visible with time, even though they may have formed the foundation of future advances. Expectations of society members has also evolved over time, with a focus on the establishment of animal husbandry practices and Canada’s livestock population from the 1920s to the 1960s, refinement in nutrition and animal breeding practices in the 1960s to the 1980s, developments in molecular biology and genomics in 1980s to the 2000s and in precision animal production, animal welfare and environmental sustainability from the 2000s to the present day. To identify the top scientists in Canada, the editors-in chief of CJAS sent out letters to every federal and university animal science department in Canada to nominate four individuals whose contributions were felt to be particularly noteworthy. This exercise clearly demonstrated that Canadian Animal Scientists have made significant contributions in all fields at a global level of recognition. This presentation will introduce you to a few of these individuals. There is no doubt that the contribution of all Canadian animal scientists has had a major role in the development and success of the Canadian livestock industry.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.954
Threshold uncertainty score0.771

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.020
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.008
Science and technology studies0.0070.004
Scholarly communication0.0110.002
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0250.011

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.262
Teacher spread0.253 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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